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Updated: Dec 10, 2025
Standardized Data Acquisition for Neuromelanin-Sensitive Magnetic Resonance Imaging of the Substantia Nigra
Published on: September 8, 2021
Normative Baseline for Radiomics in Brain MRI: Evaluating the Robustness, Regional Variations, and Reproducibility on
Umang Pandey1, Jitender Saini2, Manoj Kumar2
1Symbiosis Center for Medical Image Analysis, Symbiosis International University, Pune, India.
Background:
Radiomics in neuroimaging has gained momentum as a noninvasive prediction tool not only to differentiate between types of brain tumors, but also to create phenotypic signatures in neurological and neuropsychiatric disorders. However, there is currently little understating about the robustness and reproducibility of radiomic features in a baseline normative population.
Purpose:
To investigate the intra- and interscanner reproducibility, spatial robustness, and sensitivity of radiomics on fluid attenuation inversion recovery (FLAIR) images, which are widely used in neuro-oncology investigations.
Study Type:
Retrospective.
Population:
Three separate datasets of healthy controls: 1) 87 subjects (age range 12-64 years), 2) intrascanner three timepoints, four subjects, and 3) interscanner, eight subjects at three different sites.
Field Strength/Sequence:
T2 -weighted FLAIR at 1.5T and 3.0T.
Assessment:
Spatial variance across lobes, and their relation with age/gender, intra- and inter-scanner reproducibility (with and without site harmonization) of radiomics.
Statistical Tests:
Analysis of variance (ANOVA), interclass correlation (ICC), coefficient of variation (CoV), Bland-Altman analysis.
Results:
Analysis of data revealed no differences between genders; however, multiple radiomic features were highly associated with age (P < 0.05). Spatial variability was also evaluated where only 29.04% gray matter and 38.7% white matter features demonstrated an ICC >0.5. Furthermore, the results demonstrated intra-scanner reliability (ICC >0.5); however, inter-scanner reproducibility was poor, with ICC < 0.5 for 82% gray matter and 78.5% white matter features. The inter-scanner reliability improved (ICC < 0.5 for 39.67% gray matter and 38% white matter features) using site-harmonization techniques.
Data Conclusion:
These findings suggest that, accounting for age, spatial locations in radiomics-based analysis and use of intersite radiomics harmonization is crucial before interpreting these features for pathological inference. Level of Evidence 3. Technical Efficacy Stage 1. J. MAGN. RESON. IMAGING 2021;53:394-407.
